---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-medium
tags:
- whisper-event
- generated_from_trainer
datasets:
- audiofolder
metrics:
- wer
model-index:
- name: Whisper medium nan-tw common voice
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: audiofolder nan-tw
      type: audiofolder
      config: nan-tw
      split: test
      args: nan-tw
    metrics:
    - name: Wer
      type: wer
      value: 0.9615384615384616
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# Whisper medium nan-tw common voice

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the audiofolder nan-tw dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0141
- Model Preparation Time: 0.0121
- Wer: 0.9615
- Cer: 0.9524

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Use adamw_bnb_8bit with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Model Preparation Time | Wer     | Cer     |
|:-------------:|:------:|:----:|:---------------:|:----------------------:|:-------:|:-------:|
| 0.97          | 0.2    | 1000 | 0.7356          | 0.0121                 | 38.1731 | 38.4762 |
| 0.3044        | 1.0388 | 2000 | 0.3099          | 0.0121                 | 23.4615 | 23.9048 |
| 0.3108        | 1.2388 | 3000 | 0.1153          | 0.0121                 | 7.5     | 7.7143  |
| 0.0544        | 2.0776 | 4000 | 0.0295          | 0.0121                 | 2.3077  | 2.2857  |
| 0.0678        | 2.2776 | 5000 | 0.0141          | 0.0121                 | 0.9615  | 0.9524  |


### Framework versions

- Transformers 4.47.0.dev0
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3